Optimal scenario reduction for one- and two-stage robust optimization with discrete uncertainty in the objective
From MaRDI portal
Publication:6113355
DOI10.1016/j.ejor.2023.03.019arXiv2209.00499OpenAlexW4327924010MaRDI QIDQ6113355
No author found.
Publication date: 11 July 2023
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2209.00499
clusteringrobust optimizationapproximation algorithmsrobustness and sensitivity analysisscenario reduction
Cites Work
- Unnamed Item
- General approximation schemes for min-max (regret) versions of some (pseudo-)polynomial problems
- Approximating a two-machine flow shop scheduling under discrete scenario uncertainty
- Min-max and min-max regret versions of combinatorial optimization problems: A survey
- A cooperative local search-based algorithm for the multiple-scenario max-min knapsack problem
- Robust placement of sensors in dynamic water distribution systems
- Scenario reduction in stochastic programming
- Algorithms and uncertainty sets for data-driven robust shortest path problems
- Identifying effective scenarios in distributionally robust stochastic programs with total variation distance
- A unified framework for stochastic optimization
- A survey of adjustable robust optimization
- On scenario aggregation to approximate robust combinatorial optimization problems
- Scenario reduction algorithms in stochastic programming
- Approximating the min-max (regret) selecting items problem
- Problem-driven scenario generation: an analytical approach for stochastic programs with tail risk measure
- Decision-based scenario clustering for decision-making under uncertainty
- Representative scenario construction and preprocessing for robust combinatorial optimization problems
- Robust recoverable and two-stage selection problems
- On the complexity of a class of combinatorial optimization problems with uncertainty
This page was built for publication: Optimal scenario reduction for one- and two-stage robust optimization with discrete uncertainty in the objective